Advances in computing technologies and sensor devices encourages the incorporation of more technology in wearable sensors and personal computing systems. Such technologies offer the hope of obtaining reasonably accurate biometric data from devices that are small and unobtrusive enough to be carried and/or worn. Biometric data has particular interest in health and well-being monitoring, as well as sports performance monitoring. Biometric data is also useful for identity verification, such as data to implement two-factor authentication. However, there are traditionally many limitations encountered in designing and implementing actual systems that generate usable biometric data.
For example, a pulse oximeter is a device that measures a plethysmogram using an optical pulse, or a photoplethysmogram (PPG). A pulse oximeter pulses an LED (light emitting diode) to measure blood pulsation. The blood pulsation offers a good heart rate measurement alternative to an electrocardiogram (or electrokardiogram (EKG)). A pulse oximeter can also provide a blood pressure estimate, as well as a blood oxygen saturation level estimate. Thus, continuous PPG signal sensing in a wearable sensor can enable realtime monitoring of heartrate, blood pressure, and/or oxygen saturation in free-living conditions. Free living conditions refer to the real life scenarios encountered as a subject goes about his or her activities, instead of only obtaining measurements in controlled environments. PPG signal sensing in a non-continuous manner does not offer the information available from continuous monitoring.
However, traditional approaches to designing wearable pulse oximeters result in systems with power consumption requirements that result in poor battery life. With such traditional approaches, there is a tradeoff between extending battery life and recovering an accurate PPG signal. Typically, techniques to extend the battery life sacrifice PPG signal accuracy, and attempts to obtain better PPG signal accuracy leads to battery drain that makes PPG unsuitable for continuous sensing over a prolonged period. The LED pulsing consumes approximately 80% of system power in a conventional 32 Hz PPG design.
Thus, traditional PPG systems that run continuously at 32 Hz have unacceptable battery life. One proposal to save power is to sample at a lower rate with an intelligent sampling algorithm. However, traditional intelligent sampling algorithms require the use of an on-board random number generator, and therefore consume considerable power. Intelligent sampling saves LED power, but increases other power usage, which limits the amount of overall system power saved. The result is a system that still has poor battery performance.
Descriptions of certain details and implementations follow, including a description of the figures, which may depict some or all of the embodiments described below, as well as discussing other potential embodiments or implementations of the inventive concepts presented herein.